pacmanspikeinput.cpp

也是遗传算法的源代码

/***************************************************************************
                          pacmanspikeinput.cpp  -  description
                             -------------------
    begin                : Tue Nov 6 2001
    copyright            : (C) 2001 by Rudiger Koch
    email                : [e-mail]
 ***************************************************************************/

/***************************************************************************
 *                                                                         *
 *   This program is free software; you can redistribute it and/or modify  *
 *   it under the terms of the GNU General Public License as published by  *
 *   the Free Software Foundation; either version 2 of the License, or     *
 *   (at your option) any later version.                                   *
 *                                                                         *
 ***************************************************************************/

#include <string.h>
#include <math.h>

#include "pacmanspikeinput.h"
#include "pacman.h"

#include "amygdala/neuron.h"

PacmanSpikeInput::PacmanSpikeInput(Network *network, Pacman* pacman):
                  SpikeInput(network), timingConst(10), pacmanTimestep(300000) {
    this->pacman = pacman;
    lastMoveTime = 0;
    feeling = new Senses;
    for (unsigned int i=0; i<14; i++) lastSpike[i] = 0;
}



PacmanSpikeInput::~PacmanSpikeInput(){

}



void PacmanSpikeInput::ReadInputBuffer(){
    Network *network = pacman->getNetwork();
    AmTimeInt simTime = network->SimTime();
//    if(simTime == 0) return;
    // every 0.3 sec simTime we make a new step
    if(simTime - lastMoveTime < pacmanTimestep) return;

    memcpy((void*)feeling, pacman->step(), sizeof(Senses));
    lastMoveTime = simTime;

    // After the step we calculate the new spike frequency
    // We add .1 to every feeling to make sure we're not dividing by zero
    timeDiff[0] = (AmTimeInt) (pacmanTimestep / (feeling->upGood + .1));
    timeDiff[1] = (AmTimeInt) (pacmanTimestep / (feeling->downGood + .1));
    timeDiff[2] = (AmTimeInt) (pacmanTimestep / (feeling->leftGood + .1));
    timeDiff[3] = (AmTimeInt) (pacmanTimestep / (feeling->rightGood + .1));

    timeDiff[4] = (AmTimeInt) (pacmanTimestep / (feeling->upBad + .1));
    timeDiff[5] = (AmTimeInt) (pacmanTimestep / (feeling->downBad + .1));
    timeDiff[6] = (AmTimeInt) (pacmanTimestep / (feeling->leftBad + .1));
    timeDiff[7] = (AmTimeInt) (pacmanTimestep / (feeling->rightBad + .1));

    timeDiff[8] = (AmTimeInt) (pacmanTimestep / (feeling->pain + .1));
    timeDiff[9] = (AmTimeInt) (pacmanTimestep / (feeling->pleasure + .1));

    timeDiff[10] = (AmTimeInt) (pacmanTimestep / (feeling->upTouch + .1));
    timeDiff[11] = (AmTimeInt) (pacmanTimestep / (feeling->downTouch + .1));
    timeDiff[12] = (AmTimeInt) (pacmanTimestep / (feeling->leftTouch + .1));
    timeDiff[13] = (AmTimeInt) (pacmanTimestep / (feeling->rightTouch + .1));
    for(int i=0; i<14; i++) timeDiff[i] /= timingConst;

    // We feed the spikes into Amygdala as a rate code. The frequency is higher
    // if the particualar feeling is stronger
    for (unsigned int i=0; i<14; i++){
        for(AmTimeInt t = simTime; t - simTime < pacmanTimestep; t += timeDiff[i]){
            network->ScheduleNEvent(INPUTSPIKE, t, inputNeurons[i]);
        }
    }
}


void PacmanSpikeInput::SetInputNeurons(vector <AmIdInt> in){
    inputNeurons = in;
}